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Record W4398188169 · doi:10.1109/jestpe.2024.3403521

A Bridgeless, Stacked Switch-Pair-Based AC/DC On-Board High-Voltage EV Charger With Minimal Storage Capacitance Featuring Continuous Secondary-Side High-Frequency Rectifier Control

2024· article· en· W4398188169 on OpenAlexafffund
Siamak Derakhshan, John Lam

Bibliographic record

VenueIEEE Journal of Emerging and Selected Topics in Power Electronics · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCapacitanceElectrical engineeringRectifier (neural networks)Materials scienceVoltageCapacitorOptoelectronicsEngineeringPhysicsElectrodeComputer science

Abstract

fetched live from OpenAlex

In this paper, a fully soft-switched single-stage bridgeless stacked switches-based rectifier with reduced storage capacitance and minimized low-frequency output voltage ripple for high-voltage (HV) Electric Vehicle (EV) systems is proposed. Generally, bulky DC-link and filter electrolytic-type capacitors used in AC-DC converters reduces the converter’s reliability and life-span. To address this issue, a bridgeless AC-DC isolated converter with stacked switches configuration on both the primary and secondary sides that employs a continuous secondary side duty ratio control to reduce the low frequency output voltage ripple is presented. A front-end primary side duty ratio control for achieving power factor correction (PFC) for the integrated bridgeless boost PFC is also employed. The stacked switches-based configuration of the converter reduces the voltage stress of the switches to half of the DC-link voltage, making the converter suitable for HV battery systems. Soft-switching operation is guaranteed for all the semiconductor devices. Additionally, output voltage regulation is achieved through a Variable Frequency (VF) control on the primary-side switches. The steady-state and dynamic performance of the proposed converter and the designed control system are verified using a 1.1kW, 120V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rms</sub> /800V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dc</sub> , 100-120kHz SiC proof-of-Concept proto-type in the laboratory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.200
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2024
Admission routes2
Has abstractyes

Explore more

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